@inproceedings{yuan-etal-2020-faithfulness,
title = "On the Faithfulness for {E}-commerce Product Summarization",
author = "Yuan, Peng and
Li, Haoran and
Xu, Song and
Wu, Youzheng and
He, Xiaodong and
Zhou, Bowen",
editor = "Scott, Donia and
Bel, Nuria and
Zong, Chengqing",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.502",
doi = "10.18653/v1/2020.coling-main.502",
pages = "5712--5717",
abstract = "In this work, we present a model to generate e-commerce product summaries. The consistency between the generated summary and the product attributes is an essential criterion for the ecommerce product summarization task. To enhance the consistency, first, we encode the product attribute table to guide the process of summary generation. Second, we identify the attribute words from the vocabulary, and we constrain these attribute words can be presented in the summaries only through copying from the source, i.e., the attribute words not in the source cannot be generated. We construct a Chinese e-commerce product summarization dataset, and the experimental results on this dataset demonstrate that our models significantly improve the faithfulness.",
}
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<abstract>In this work, we present a model to generate e-commerce product summaries. The consistency between the generated summary and the product attributes is an essential criterion for the ecommerce product summarization task. To enhance the consistency, first, we encode the product attribute table to guide the process of summary generation. Second, we identify the attribute words from the vocabulary, and we constrain these attribute words can be presented in the summaries only through copying from the source, i.e., the attribute words not in the source cannot be generated. We construct a Chinese e-commerce product summarization dataset, and the experimental results on this dataset demonstrate that our models significantly improve the faithfulness.</abstract>
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%0 Conference Proceedings
%T On the Faithfulness for E-commerce Product Summarization
%A Yuan, Peng
%A Li, Haoran
%A Xu, Song
%A Wu, Youzheng
%A He, Xiaodong
%A Zhou, Bowen
%Y Scott, Donia
%Y Bel, Nuria
%Y Zong, Chengqing
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 December
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F yuan-etal-2020-faithfulness
%X In this work, we present a model to generate e-commerce product summaries. The consistency between the generated summary and the product attributes is an essential criterion for the ecommerce product summarization task. To enhance the consistency, first, we encode the product attribute table to guide the process of summary generation. Second, we identify the attribute words from the vocabulary, and we constrain these attribute words can be presented in the summaries only through copying from the source, i.e., the attribute words not in the source cannot be generated. We construct a Chinese e-commerce product summarization dataset, and the experimental results on this dataset demonstrate that our models significantly improve the faithfulness.
%R 10.18653/v1/2020.coling-main.502
%U https://aclanthology.org/2020.coling-main.502
%U https://doi.org/10.18653/v1/2020.coling-main.502
%P 5712-5717
Markdown (Informal)
[On the Faithfulness for E-commerce Product Summarization](https://aclanthology.org/2020.coling-main.502) (Yuan et al., COLING 2020)
ACL
- Peng Yuan, Haoran Li, Song Xu, Youzheng Wu, Xiaodong He, and Bowen Zhou. 2020. On the Faithfulness for E-commerce Product Summarization. In Proceedings of the 28th International Conference on Computational Linguistics, pages 5712–5717, Barcelona, Spain (Online). International Committee on Computational Linguistics.